EchoPro Kriging mesh Workflow#

Import libraries and configure the Jupyter notebook#

# libraries used in the Notebook
import matplotlib.pyplot as plt
import geopandas
import folium

# Python version of EchoPro
import EchoPro

# obtain all visualization routines
from EchoPro.visualization import plot_layered_points, plot_points

Set up EchoPro for a specific survey year#

Initialize EchoPro object using configuration files#

  • initialization_config.yml – parameters independent of survey year

  • survey_year_2019_config.yml – parameters specific to survey year

  • source – Define the region of data to use e.g. US, CAN, US & CAN

  • exclude_age1 – States whether age 1 hake should be included in analysis.

%%time 
survey_2019 = EchoPro.Survey(init_file_path='../config_files/initialization_config.yml',
                             survey_year_file_path='../config_files/survey_year_2019_config.yml',
                             source=3,
                             exclude_age1=True)

A full check of the initialization file contents needs to be done!
A check of the survey year file contents needs to be done!
CPU times: user 5.36 ms, sys: 586 µs, total: 5.95 ms
Wall time: 6.03 ms

Load and process input data#

  • This data is stored in survey_2019

%%time 
survey_2019.load_survey_data()

CPU times: user 1.39 s, sys: 16.9 ms, total: 1.41 s
Wall time: 1.41 s

Compute the areal biomass density#

  • The areal biomass density is stored in survey_2019.bio_calc.transect_results_gdf as biomass_density_adult

%%time
survey_2019.compute_biomass_density()

CPU times: user 343 ms, sys: 0 ns, total: 343 ms
Wall time: 343 ms

Obtain Kriging Mesh Data#

Access Kriging mesh object#

  • Reads mesh data files specified by survey_2019

krig_mesh = survey_2019.get_kriging_mesh()

Plot the Mesh, Transects and smoothed isobath contour#

  • Generate interactive map using the Folium package

  • Mesh points are in gray

  • Transect points are represented by a changing color gradient

  • Smoothed contour points (200m isobath) are in blue

fmap = plot_layered_points(krig_mesh)
fmap
Make this Notebook Trusted to load map: File -> Trust Notebook

Obtain reduced mesh#

  • EchoPro allows the user to select only those mesh points that are contained in a polygon surrounding the transect points

    • For more information on the method, please see the Notes section in the doc string for KrigingMesh.get_polygon_of_transects

# obtain the polygon of the transects 
transect_polygon = krig_mesh.get_polygon_of_transects(survey_2019.bio_calc.transect_results_gdf, 
                                                      n_close=4, nm_to_buffer=1.25)

# plot transect points 
fmap_polygon = plot_points(survey_2019.bio_calc.transect_results_gdf, cmap_column='transect_num', color='hex')

# Add polygon to folium map and display it
fmap_polygon.add_child(folium.GeoJson(transect_polygon))
Make this Notebook Trusted to load map: File -> Trust Notebook

Select mesh points within polygon#

  • Using the constructed polygon we can get those mesh points that are within it

# get reduced mesh based off of a polygon
reduced_mesh_gdf = krig_mesh.reduce_grid_points(transect_polygon)

# plot the reduced mesh points
fmap_reduced = plot_points(reduced_mesh_gdf, color='red')

# plot the transect points 
fmap_reduced = plot_points(survey_2019.bio_calc.transect_results_gdf, fmap_reduced, 
                           cmap_column='transect_num', color='hex')

# display transects and reduced mesh
fmap_reduced
Make this Notebook Trusted to load map: File -> Trust Notebook